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Semantic Network Analytics
Semantic analytics, also termed ''semantic relatedness'', is the use of ontologies to analyze content in web resources. This field of research combines text analytics and Semantic Web technologies like RDF. Semantic analytics measures the relatedness of different ontological concepts. Some academic research groups that have active project in this area include Kno.e.sis Center at Wright State University among others. History An important milestone in the beginning of semantic analytics occurred in 1996, although the historical progression of these algorithms is largely subjective. In his seminal study publication, Philip Resnik established that computers have the capacity to emulate human judgement. Spanning the publications of multiple journals, improvements to the accuracy of general semantic analytic computations all claimed to revolutionize the field. However, the lack of a standard terminology throughout the late 1990s was the cause of much miscommunication. This prompted Bu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology (information Science)
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as ''applied ontology''. Every academic discipline or field, in creating its terminology, thereby lays the groundwork for an ontology. Each uses ontological assumptions to frame explicit theories, research and applications. Improved ontologies may improve problem solving within that domain, interoperability of data systems, and discoverability of data. Translating research papers within every field is a problem made easier when experts from different countries mainta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. Major tasks in natural language processing are speech recognition, text classification, natural-language understanding, natural language understanding, and natural language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Similarity
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving". Computationally, semantic similarity can be estimated by defining a topological similarity, by using ontologies to define the distance between terms/concepts. For example, a naive metric for the comparison of concepts ord ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Brand Score
The Semantic Brand Score (SBS) is a measure of brand importance that is calculated on textual data. The measure is rooted in graph theory and partly connected to Keller's conceptualization of brand equity. It is calculated by converting texts into word or semantic networks and analyzing three key aspects: the frequency with which a brand name is mentioned (prevalence), the extent to which it is linked to distinctive and uncommon terms in the discourse (diversity), and its potential role as a bridge that connects otherwise unconnected or weakly connected terms or concepts (connectivity). The metric has also been used more broadly as an indicator of semantic importance, with varying objectives, by examining different text sources, such as newspaper articles, online forums, scientific papers, or social media posts. Definition and calculation Pre-processing To compute the Semantic Brand Score, it is necessary to convert the analyzed texts into word networks, i.e., graphs where ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Relationship Extraction
A relationship extraction task requires the detection and classification of semantic relationship mentions within a set of artifacts, typically from text or XML documents. The task is very similar to that of information extraction (IE), but IE additionally requires the removal of repeated relations (other) and generally refers to the extraction of many different relationships. Concept and applications The concept of relationship extraction was first introduced during the 7th Message Understanding Conference in 1998. Relationship extraction involves the identification of relations between entities and it usually focuses on the extraction of binary relations. Application domains where relationship extraction is useful include gene-disease relationships, protein-protein interaction etc. Current relationship extraction studies use machine learning technologies, which approach relationship extraction as a classification problem. Never-Ending Language Learning is a semantic m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Scholar
Semantic Scholar is a research tool for scientific literature. It is developed at the Allen Institute for AI and was publicly released in November 2015. Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. The Semantic Scholar team is actively researching the use of artificial intelligence in natural language processing, machine learning, human–computer interaction, and information retrieval. Semantic Scholar began as a database for the topics of computer science, geoscience, and neuroscience. In 2017, the system began including biomedical literature in its corpus. , it includes over 200 million publications from all fields of science. Technology Semantic Scholar provides a one-sentence summary of scientific literature. One of its aims was to address the challenge of reading numerous titles and lengthy abstracts on mobile devices. It also seeks t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Management
Knowledge management (KM) is the set of procedures for producing, disseminating, utilizing, and overseeing an organization's knowledge and data. It alludes to a multidisciplinary strategy that maximizes knowledge utilization to accomplish organizational goals. Courses in business administration, information systems, management, libraries, and information science are all part of knowledge management, a discipline that has been around since 1991. Information and media, computer science, public health, and public policy are some of the other disciplines that may contribute to KM research. Numerous academic institutions provide master's degrees specifically focused on knowledge management. As a component of their IT, human resource management, or business strategy departments, many large corporations, government agencies, and nonprofit organizations have resources devoted to internal knowledge management initiatives. These organizations receive KM guidance from a number of consulting ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cortana (virtual Assistant)
Cortana was a virtual assistant developed by Microsoft that used the Bing search engine to perform tasks such as setting reminders and answering questions for users. Cortana was available in English, Portuguese, French, German, Italian, Spanish, Chinese, and Japanese language editions, depending on the software platform and region in which it was used. In 2019, Microsoft began reducing the prevalence of Cortana and converting it from an assistant into different software integrations. It was split from the Windows 10 search bar in April 2019. In January 2020, the Cortana mobile app was removed from certain markets, and on March 31, 2021, the Cortana mobile app was shut down globally. On June 2, 2023, Microsoft announced that support for the Cortana standalone app on Microsoft Windows would end in late 2023 and would be replaced by Microsoft Copilot, an AI chatbot. Support for Cortana in the Microsoft Outlook and Microsoft 365 mobile apps was discontinued in fall of 2023. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Assistant
Google Assistant is a virtual assistant software application developed by Google that is primarily available on home automation and mobile devices. Based on artificial intelligence, Google Assistant can engage in two-way conversations, unlike the company's previous virtual assistant, Google Now. Google Assistant debuted in 2016 as part of Google's messaging app Allo, and its voice-activated speaker Google Nest. After a period of exclusivity on the Google Pixel smartphones, it was deployed on other Android devices starting in February 2017, including third-party smartphones and Android Wear (now Wear OS), and was released as a standalone app on the iOS operating system in May 2017. Alongside the announcement of a software development kit in April 2017, Assistant has been further extended to support a large variety of devices, including cars and third-party smart home appliances. The functionality of Assistant can also be enhanced by third-party developers. At CES 2018, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Amazon Alexa
Amazon Alexa is a virtual assistant technology marketed by Amazon and implemented in software applications for smart phones, tablets, wireless smart speakers, and other electronic appliances. Alexa was largely developed from a Polish speech synthesizer named Ivona, acquired by Amazon in January 24, 2013. Alexa was first used in the Amazon Echo smart speaker and the Amazon Echo Dot, Echo Studio and Amazon Tap speakers developed by Amazon Lab126. It is capable of natural language processing for tasks such as voice interaction, music playback, creating to-do lists, setting alarms, streaming podcasts, playing audiobooks, providing weather, traffic, sports, other real-time information and news. Alexa can also control several smart devices as a home automation system. Alexa's capabilities may be extended by installing "skills" (additional functionality developed by third-party vendors, in other settings more commonly called apps) such as weather programs and audio feature ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Base
In computer science, a knowledge base (KB) is a set of sentences, each sentence given in a knowledge representation language, with interfaces to tell new sentences and to ask questions about what is known, where either of these interfaces might use inference. It is a technology used to store complex structured data used by a computer system. The initial use of the term was in connection with expert systems, which were the first knowledge-based systems. Original usage of the term The original use of the term knowledge base was to describe one of the two sub-systems of an expert system. A knowledge-based system consists of a knowledge-base representing facts about the world and ways of reasoning about those facts to deduce new facts or highlight inconsistencies. Properties The term "knowledge-base" was coined to distinguish this form of knowledge store from the more common and widely used term ''database''. During the 1970s, virtually all large management information sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
